Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -123,7 +123,7 @@ with gr.Blocks() as demo:
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max_steps = gr.Slider(label="Max Steps", minimum=50, maximum=200, value=200)
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learning_rate = gr.Slider(label="Learning Rate", minimum=0.01, maximum=0.5, value=0.02)
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optimization_steps = gr.Slider(label="Optimization Steps", minimum=1, maximum=10, value=1)
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-
inverseproblem = gr.Checkbox(label="Apply mask on pixel space", value=False, info="Enables inverse problem formulation for inpainting by masking the RGB image itself. Hence, to avoid artifacts we increase the mask size manually during inference.")
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mask_input = gr.Image(
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type="pil",
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label="Optional Mask",
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@@ -268,7 +268,7 @@ with gr.Blocks() as demo:
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200, # max_steps
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0.02, # learning_rate
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10, # optimization_steps
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-
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],
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[
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"./saved_results/20241129_212052/input.png", # image with mask
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@@ -281,7 +281,7 @@ with gr.Blocks() as demo:
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200, # max_steps
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0.02, # learning_rate
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10, # optimization_steps
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-
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],
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[
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"./saved_results/20241129_212155/input.png", # image with mask
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@@ -294,7 +294,7 @@ with gr.Blocks() as demo:
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200, # max_steps
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0.02, # learning_rate
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10, # optimization_steps
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-
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],
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],
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inputs=[
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max_steps = gr.Slider(label="Max Steps", minimum=50, maximum=200, value=200)
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learning_rate = gr.Slider(label="Learning Rate", minimum=0.01, maximum=0.5, value=0.02)
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optimization_steps = gr.Slider(label="Optimization Steps", minimum=1, maximum=10, value=1)
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+
inverseproblem = gr.Checkbox(label="Apply mask on pixel space (does not work well with HF ZeroGPU)", value=False, info="Enables inverse problem formulation for inpainting by masking the RGB image itself. Hence, to avoid artifacts we increase the mask size manually during inference.")
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mask_input = gr.Image(
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type="pil",
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label="Optional Mask",
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200, # max_steps
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0.02, # learning_rate
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10, # optimization_steps
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False,
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],
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[
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"./saved_results/20241129_212052/input.png", # image with mask
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200, # max_steps
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0.02, # learning_rate
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10, # optimization_steps
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False,
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],
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[
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"./saved_results/20241129_212155/input.png", # image with mask
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200, # max_steps
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0.02, # learning_rate
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10, # optimization_steps
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+
False,
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],
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],
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inputs=[
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